Revamping Building Extraction with Yolov8: A Multi-Domain Assessment in Bangkok's Diverse Land-Use-Types

Accurate building footprint data is indispensable for urban planning, and database creation but, existing building extraction models, primarily originating from developed countries, face limitations when applied to rural regions or developing countries due to intricate building patterns across diverse land-use types. This research addresses these challenges, focusing on a case study of Bangkok province, Thailand. We introduce a comprehensive methodology that develops seven specialized YOLOv8 and YOLOv7 models, trained from scratch to accommodate distinct land-use types and their unique building patterns. A multi-domain assessment is conducted across various land-use types to assess the accuracy, applicability, and adaptability of these models. The findings offer a valuable template for future research in building extraction from satellite imagery, advancing instance segmentation techniques, and enhancing their practical utility across diverse land-use scenarios.